Senior Applied Scientist, Amazon Leo Data Science Platform
The Role
The position requires hands-on expertise in Analytics to identify and isolate issues, Statistical Modeling and traditional Machine Learning, the ability to write queries to aid in data extraction, and the ability to productionalize models. This role is a self-sufficient scientist that can source data, build and evaluate models, and ultimately take those models and rules to deployment. You should have excellent communication skills and be able to work with stakeholders at all levels. Above all, you should be a passionate, hard-working, and creative person who loves creating business impact, loves solving difficult problems, and doesn’t mind getting involved in the details.
Key job responsibilities
- Identify and isolate issues using Analytics
- Build and evaluate machine learning models
- Productionalize models
- Collaborate with internal stakeholders to identify and address fraud vulnerabilities
- Develop rules and ML models to prevent Customer Terminal (CT) usage fraud and abuse
- Leverage customer-obsession skills to ensure user experience is not adversely affected by mechanisms designed
About the team
The Amazon Leo Data Science Platform team builds services to ingest, transform, and aggregate data from various devices in Leo Network, and auto detect, diagnose, and resolve issues. We use ML technology to monitor customer experience and prevent fraud and abuse.
Basic Qualifications
- 3+ years of building machine learning models for business applications
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
Preferred Qualifications
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.